Revolutionizing LLM Verification: A Novel Approach to Combat 'Reading Pretenses'

This article introduces a groundbreaking system designed to prevent Generative AI from feigning comprehension of documents. By leveraging SHA256 hashing and mechanical scoring, the system ensures verifiable evidence of actual reading, promising a new era of trust in LLM outputs. It's a fantastic step towards enhancing the reliability of AI systems!

• •Employs SHA256 hashing to verify that the LLM has truly read and processed the entire document, not just parts of it.
• •Divides the document into sections (head, middle, tail) to ensure the LLM engages with all parts, preventing superficial reading.
• •Uses mechanical scoring to avoid the biases that come with letting an LLM evaluate another.